Software Optimization Engineer (m/f/d)

Summary

At Apple, our Platform Architecture group is responsible for connecting our hardware and software into one unified system. You’ll collaborate with engineers across Apple to design how all of our technologies work in unison, drive development of our renowned system-on-a-chip architecture and develop forward-looking prototype systems and software. Our team is driving performance enhancements in application and system software and developing novel algorithms to deliver integrated, highly optimized solutions based on Apple Silicon. In this role, you will analyze existing and new workloads to identify performance bottlenecks in the hardware and/or software. Working with your colleagues, you will address performance limitations and provide recommendations for Apple hardware and software improvements. In addition to working directly with developers, you will identify patterns of performance challenges on Apple silicon, emerging new usage models, and provide feedback to the silicon and software teams for potential improvements.

Description

Analyze AI/ML and compute workloads to identify performance bottlenecks across various running devices, including GPU and CPU. Implement and suggest improvements to remove identified bottlenecks. Build targeted microbenchmarks to evaluate hardware-specific performance characteristics and understand the strengths and weaknesses of various devices and usage patterns. Create optimized implementations of software workloads on Apple Silicon, including GPU and CPU, utilizing the latest instruction sets and frameworks. Collaborate with Platform Architecture teams to create performance models of emerging application techniques and analyze system architecture trade-offs. Work closely with software development tools teams to deliver advanced performance analysis instruments, optimized libraries, and frameworks.

Minimum Qualifications

Bachelor’s degree or equivalent job-related experience in Computer Engineering, Computer Science, or a related field. Strong foundation in computer architecture fundamentals, hardware/software co-design, and machine learning concepts. Hands-on experience (through internships, academic research, or intensive coursework) in software performance optimization, performance analysis, and microbenchmarking. Strong proficiency in C/C++ family of programming languages and scripting languages such as Python. Experience with AI/ML frameworks, graphics libraries, or HPC performance benchmarks and workloads.

Preferred Qualifications

Master’s degree (or currently completing an MSc) in Computer Science, Computer Engineering, Electrical Engineering, or a related field. Experience developing for and benchmarking GPUs using platform-specific languages and APIs (e.g., Metal/MSL, Vulkan, CUDA, DirectX/HLSL, etc.). Demonstrated technical excellence, such as high academic standing, success in algorithmic/coding competitions, or contributions to publicly released developer tools. Exceptional technical aptitude, curiosity, and communication skills, with a demonstrated ability to mentor others (e.g., teaching assistantships) and collaborate effectively with cross-functional teams.